Mining marketing intelligence from online reviews using sentiment analysis
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[1] Richong Zhang,et al. Helping E-Commerce Consumers Make Good Purchase Decisions: A User Reviews-Based Approach , 2009, MCETECH.
[2] Eric K. Ringger,et al. Pulse: Mining Customer Opinions from Free Text , 2005, IDA.
[3] Richard Colbaugh,et al. Estimating sentiment orientation in social media for intelligence monitoring and analysis , 2010, 2010 IEEE International Conference on Intelligence and Security Informatics.
[4] Razvan C. Bunescu,et al. Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques , 2003, Third IEEE International Conference on Data Mining.
[5] Seong Joon Yoo,et al. Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews , 2012, Expert Syst. Appl..
[6] Bin Gu,et al. Do online reviews matter? - An empirical investigation of panel data , 2008, Decis. Support Syst..
[7] Vibhu O. Mittal,et al. Comparative Experiments on Sentiment Classification for Online Product Reviews , 2006, AAAI.
[8] Eric T. Bradlow,et al. Automated Marketing Research Using Online Customer Reviews , 2011 .
[9] Philippe Duverger,et al. Curvilinear Effects of User-Generated Content on Hotels’ Market Share , 2013 .
[10] Bo Pang,et al. Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales , 2005, ACL.
[11] Bo Pang,et al. A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.
[12] Steven M. Shugan,et al. Film Critics: Influencers or Predictors? , 1997 .
[13] David Schuff,et al. What Makes a Helpful Review? A Study of Customer Reviews on Amazon.com , 2010 .
[14] Donnavieve N. Smith,et al. Online Peer and Editorial Recommendations, Trust, and Choice in Virtual Markets , 2005 .
[15] B. Pan,et al. A retrospective view of electronic word-of-mouth in hospitality and tourism management , 2017 .
[16] R. Kozinets. E-tribalized Marketing?: The Strategic Implications of Virtual Communities of Consumption , 1999 .
[17] Maite Taboada,et al. Lexicon-Based Methods for Sentiment Analysis , 2011, CL.
[18] Robert M. Schindler,et al. Internet forums as influential sources of consumer information , 2001 .
[19] Lina Zhou,et al. Movie Review Mining: a Comparison between Supervised and Unsupervised Classification Approaches , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.
[20] K. File,et al. Word-of-Mouth Effects in Professional Services Buyer Behaviour , 1994 .
[21] Chrysanthos Dellarocas,et al. Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms , 2004, Manag. Sci..
[22] P. Herr,et al. Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective , 1991 .
[23] Songbo Tan,et al. A survey on sentiment detection of reviews , 2009, Expert Syst. Appl..
[24] David M. Pennock,et al. Mining the peanut gallery: opinion extraction and semantic classification of product reviews , 2003, WWW '03.
[25] Bing Liu,et al. Opinion observer: analyzing and comparing opinions on the Web , 2005, WWW '05.
[26] Ruwei Dai,et al. AMAZING: A sentiment mining and retrieval system , 2009, Expert Syst. Appl..
[27] Khairullah Khan,et al. Sentence based sentiment classification from online customer reviews , 2010, FIT.
[28] Sangwon Park,et al. What makes a useful online review? Implication for travel product websites. , 2015 .
[29] Nada Nasr Bechwati,et al. Word of Mouse , 2008 .
[30] Thorsten Joachims,et al. Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.
[31] P. Chatterjee,et al. Online Reviews: Do Consumers Use Them? , 2006 .
[32] Bing Liu,et al. Opinion spam and analysis , 2008, WSDM '08.
[33] Bo Pang,et al. Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.
[34] J. Crotts,et al. Travel Blogs and the Implications for Destination Marketing , 2007 .
[35] Rudy Prabowo,et al. Sentiment analysis: A combined approach , 2009, J. Informetrics.
[36] Michael L. Littman,et al. Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus , 2002, ArXiv.
[37] Li Chen,et al. Comparison of feature-level learning methods for mining online consumer reviews , 2012, Expert Syst. Appl..
[38] Stephen Shaoyi Liao,et al. Mining comparative opinions from customer reviews for Competitive Intelligence , 2011, Decis. Support Syst..
[39] Zili Zhang,et al. Sentiment classification of Internet restaurant reviews written in Cantonese , 2011, Expert Syst. Appl..
[40] Yue Lu,et al. Latent aspect rating analysis on review text data: a rating regression approach , 2010, KDD.
[41] Chen Wu,et al. Deriving collective intelligence from reviews on the social Web using a supervised learning approach , 2011, Expert Syst. Appl..
[42] Kathleen R. McKeown,et al. Predicting the semantic orientation of adjectives , 1997 .
[43] Marshall S. Smith,et al. The general inquirer: A computer approach to content analysis. , 1967 .
[44] Daniel Zeng,et al. Fine-grained opinion mining by integrating multiple review sources , 2010 .
[45] Wen-Chin Tsao,et al. Compliance with eWOM: the influence of hotel reviews on booking intention from the perspective of consumer conformity. , 2015 .
[46] O. Holsti. Content Analysis for the Social Sciences and Humanities , 1969 .
[47] Nan Hu,et al. Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales , 2014, Decis. Support Syst..
[48] Philip J. Stone,et al. Extracting Information. (Book Reviews: The General Inquirer. A Computer Approach to Content Analysis) , 1967 .
[49] Colin Jevons,et al. Memo to Marketers: Quantitative Evidence for Change , 2012, Journal of Advertising Research.
[50] Huaping Chen,et al. Credibility of Electronic Word-of-Mouth: Informational and Normative Determinants of On-line Consumer Recommendations , 2009, Int. J. Electron. Commer..
[51] Japinder Singh,et al. Feature-based opinion mining and ranking , 2012, J. Comput. Syst. Sci..
[52] Jacob Goldenberg,et al. Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth , 2001 .
[53] Jun Yang,et al. A Computer Aided Content Analysis of Online Reviews , 2011, J. Comput. Inf. Syst..
[54] S. Sen,et al. Why are you telling me this? An examination into negative consumer reviews on the Web , 2007 .
[55] Roland Schegg,et al. The interactive effects of online reviews on the determinants of Swiss hotel performance: a neural network analysis. , 2015 .
[56] Lorin M. Hitt,et al. Self Selection and Information Role of Online Product Reviews , 2007, Inf. Syst. Res..
[57] P. Bone. Word-of-mouth effects on short-term and long-term product judgments , 1995 .
[58] Yong Liu,et al. When do Third-Party Product Reviews Affect Firm Value and what can Firms Do? The Case of Media Critics and Professional Movie Reviews , 2012 .
[59] Jin Zhang,et al. An empirical study of sentiment analysis for chinese documents , 2008, Expert Syst. Appl..
[60] I. Vermeulen,et al. Tried and tested: The impact of online hotel reviews on consumer consideration , 2009 .
[61] Alok N. Choudhary,et al. Voice of the Customers: Mining Online Customer Reviews for Product Feature-based Ranking , 2010, WOSN.
[62] Chih-Ping Wei,et al. Understanding what concerns consumers: a semantic approach to product feature extraction from consumer reviews , 2010, Inf. Syst. E Bus. Manag..
[63] Shubhamoy Dey,et al. A comparative study of feature selection and machine learning techniques for sentiment analysis , 2012, RACS.
[64] Manfred Klenner,et al. PolArt: A Robust Tool for Sentiment Analysis , 2009, NODALIDA.
[65] Q. Ye,et al. The impact of e-word-of-mouth on the online popularity of restaurants: a comparison of consumer reviews and editor reviews. , 2010 .
[66] Grzegorz Kondrak,et al. A Comparison of Sentiment Analysis Techniques: Polarizing Movie Blogs , 2008, Canadian Conference on AI.
[67] Pei-Yu Sharon Chen,et al. The Impact of Online Recommendations and Consumer Feedback on Sales , 2004, ICIS.
[68] Lillian Lee,et al. Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..
[69] P. J. Sher,et al. Consumer skepticism and online reviews: An Elaboration Likelihood Model perspective , 2009 .
[70] Michael L. Littman,et al. Measuring praise and criticism: Inference of semantic orientation from association , 2003, TOIS.
[71] Deepak Khazanchi,et al. An Empirical Study of Online Word of Mouth as a Predictor for Multi-product Category e-Commerce Sales , 2008, Electron. Mark..
[72] Bing Liu,et al. Mining and summarizing customer reviews , 2004, KDD.
[73] Cheol Park,et al. Information direction, website reputation and eWOM effect: A moderating role of product type , 2009 .
[74] Marsha L. Richins. Negative Word-of-Mouth by Dissatisfied Consumers: A Pilot Study , 1983 .
[75] Qiang Ye,et al. Sentiment classification of online reviews to travel destinations by supervised machine learning approaches , 2009, Expert Syst. Appl..
[76] Tzu-Liang Tseng,et al. Discovering business intelligence from online product reviews: A rule-induction framework , 2012, Expert Syst. Appl..
[77] Jason Q. Zhang,et al. When does electronic word-of-mouth matter? A study of consumer product reviews☆ , 2010 .
[78] S. Sénécal,et al. The influence of online product recommendations on consumers' online choices , 2004 .
[79] B. Gu,et al. The impact of online user reviews on hotel room sales , 2009 .
[80] Pranjal Gupta,et al. How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective , 2010 .
[81] Hua Xu,et al. Weakness Finder: Find product weakness from Chinese reviews by using aspects based sentiment analysis , 2012, Expert Syst. Appl..
[82] Alistair Kennedy,et al. SENTIMENT CLASSIFICATION of MOVIE REVIEWS USING CONTEXTUAL VALENCE SHIFTERS , 2006, Comput. Intell..
[83] C. Vogt,et al. The Effects of Integrating Advertising and Negative Word‐of‐Mouth Communications on Message Processing and Response , 1995 .
[84] Katerina Veselovská. Sentence-level sentiment analysis in Czech , 2012, WIMS '12.
[85] Michael Gamon,et al. Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis , 2004, COLING.
[86] X. Zhang,et al. Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics , 2010 .
[87] Wei Chen,et al. The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings , 2011, Comput. Hum. Behav..
[88] Peter D. Turney. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews , 2002, ACL.
[89] Juan Luis Nicolau,et al. Asymmetric effects of online consumer reviews , 2015 .
[90] Felipe Bravo-Marquez,et al. A novel deterministic approach for aspect-based opinion mining in tourism products reviews , 2014, Expert Syst. Appl..